June 07, 2018

Data Should Tell the Whole Truth and Nothing But the Truth

Disclaimer: I didn’t make this image, cartoon credit to Timo Elliott

Ronald Coase, Nobel Prize winning Economist, said that ‘if you torture the data long enough, it will confess to anything’.

Data analysts are under constant pressure to make the data fit the decisions, rather than letting the data speak for itself. This thankless task means having to rework the data and tweak the narrative to present the answer that the people in charge want to see.

Working around this type of confirmation bias can be detrimental to an organisation. You’d have to ask yourself, what insights are you really getting from your data? And can you rely on the business decisions you are making, which are almost wholly based on your (or your company’s) pre-existing beliefs?

And what if the data analyst is working with data that hasn’t been collected for the task that they’re on? It could be that data was collected for some separate internal project and was repurposed to a completely different task, rendering the data mostly unfit for that new purpose, not to mention potential data quality issues.

If you chose to take a methodical approach instead, you’d pick a hypothesis, or an outcome, and decide what data you’d need to collect to reach a conclusion. Doing things the other way around is inefficient and unhelpful. In such cases the cliché rings true – “garbage in, garbage out”.

You’re not really doing your organisation any favours working this way. Rather than coercing your data to confess, allow it to tell you the truth.

Maybe you have a different problem, maybe you don’t know how to work the data you have, to tell a story of patterns and trends that would provide valuable information within your business. Information that wasn’t pre-conceived.

Or maybe you’re not sure what you’d need to collect to get the results, to prove or disprove a theory. As Sherlock Holmes put it “It is a capital mistake to theorise before one has data”. Yes I know he’s not real, but he is right.

Small companies, we find, will usually lack the resources (and certainly will not have data analysts at hand) to conduct a thorough analysis.

Sometimes outsourcing the work is the way to go.

If you look after data but your job does not involve data manipulation, you can’t be expected to know how to solve data problems by yourself.

If you’re just a dabbler and you enjoy playing round with Excel now and again but are not equipped to perform deep analysis, you might be better off leaving things with the experts.

At Acuate we have exactly the team of experts you need, with the kind of knowledge that will drive your data projects to excellence.

We use all the latest technologies and methods to create a bespoke solution tailored to your needs. We will ensure your data is of good quality and relevant, and we’ll do the analytical work so you can sit back and relax in the knowledge that the insights you’ll be getting will fire up great business decisions.

Get in touch with us, tell us what you need and we’ll show you how we can help.

Comments

Ronald Coase, Nobel Prize winning Economist, said that ‘if you torture the data long enough, it will confess to anything’.

Data analysts are under constant pressure to make the data fit the decisions, rather than letting the data speak for itself. This thankless task means having to rework the data and tweak the narrative to present the answer that the people in charge want to see.

Working around this type of confirmation bias can be detrimental to an organisation. You’d have to ask yourself, what insights are you really getting from your data? And can you rely on the business decisions you are making, which are almost wholly based on your (or your company’s) pre-existing beliefs?

And what if the data analyst is working with data that hasn’t been collected for the task that they’re on? It could be that data was collected for some separate internal project and was repurposed to a completely different task, rendering the data mostly unfit for that new purpose, not to mention potential data quality issues.

If you chose to take a methodical approach instead, you’d pick a hypothesis, or an outcome, and decide what data you’d need to collect to reach a conclusion. Doing things the other way around is inefficient and unhelpful. In such cases the cliché rings true – “garbage in, garbage out”.

You’re not really doing your organisation any favours working this way. Rather than coercing your data to confess, allow it to tell you the truth.

Maybe you have a different problem, maybe you don’t know how to work the data you have, to tell a story of patterns and trends that would provide valuable information within your business. Information that wasn’t pre-conceived.

Or maybe you’re not sure what you’d need to collect to get the results, to prove or disprove a theory. As Sherlock Holmes put it “It is a capital mistake to theorise before one has data”. Yes I know he’s not real, but he is right.

Small companies, we find, will usually lack the resources (and certainly will not have data analysts at hand) to conduct a thorough analysis.

Sometimes outsourcing the work is the way to go.

If you look after data but your job does not involve data manipulation, you can’t be expected to know how to solve data problems by yourself.

If you’re just a dabbler and you enjoy playing round with Excel now and again but are not equipped to perform deep analysis, you might be better off leaving things with the experts.

At Acuate we have exactly the team of experts you need, with the kind of knowledge that will drive your data projects to excellence.

We use all the latest technologies and methods to create a bespoke solution tailored to your needs. We will ensure your data is of good quality and relevant, and we’ll do the analytical work so you can sit back and relax in the knowledge that the insights you’ll be getting will fire up great business decisions.

Get in touch with us, tell us what you need and we’ll show you how we can help.